Jun 2024 – Nov 2025 · 1 yr 5 mos

• ● Managing a $5M annual engagement for Fortune 20 retail & CPG clients
• ● Collaborated with Business Unit heads and the Growth team in the CEO’s office to identify,
• pitch, and convert new business opportunities, driving $1M in deals over 9 months
• ● Leading Gen AI, ML, and various data science and analytics development projects for retail
• and CPG verticals as a Product & Data Science Manager
• ● Managing 60+ team members across business units, ensuring delivery excellence and
• constant innovation
• Key Achievements:
• ● R&D Cost Innovation Tool: Reduced CPG production costs for the R&D team by $10M within
• 6 months by leading the development of a cost-innovation tool as Product Manager; enabled
• 75% reduction in time-to-test and increased recipe testing capacity by 10x through a scalable
• framework for simulating multiple recipes and packaging designs at the click of a button
• ● Gen AI Chatbot (Slack Integration): Led as Product Manager to deliver a Slack-integrated
• GenAI bot using agentic AI, boosting productivity by 75% for data scientists and business
• heads at a Fortune 20 retailer; enabled accurate resolution of descriptive, inquisitive,
• prescriptive, and predictive queries with 99% accuracy
• ● Next Best Action Framework: Drove $50M revenue uplift through customer-centric,
• personalized marketing using deep reinforcement learning for a Fortune 20 retailer, helping
• them move away from product-centric marketing

Aug 2022 – Jun 2024 · 1 yr 10 mos

• Business development for MuSigma across new business clients and identifying their problems to pitch the best desired solution:
•  Converted projects on Website optimisation, Customer lifetime value with a fortune 20 retailer across different marketing verticals
• Leading a marketing optimisation project on Audience Governance for a home improvement retail giant:
•  Lead the EDA based analysis on customer targeting strategy for business partners to help them drive better iROAS from marketing campaigns ensuring best practices of A/B testing have been maintained while testing the recommendations
•  2x revenue generation by halving the money spent on audience targeting
• Leading Customer Value modelling to enhance better targeting and priortiztion of audience for campaigns:
•  Lead the effort on building a predictive modelling framework to identify the monetary value of a customer in next 1 year laying down the whole solution pipeline idea and being involved in problem solving approach throughout execution of the project
•  40% increase from a sales objective campaign by targeting higher revenue generating higher propensity audience
• Leading setting of model governance framework(MlOps):
•  Lead the effort in developing an automated framework to build models, validate and deploy them and most importantly regular monitoring and tracking of the model performance
•  Lay down business and in model metrics rule to laydown red flag rules for re triggering of models
•  Enabled savings of 20M$ by early flagging of a marketing model
• Lead a dare engagement project on Web Page Enhancement:
•  Lead the effort to help setup a PIP page enhancement framework including clustering and predictive modelling algorithm to club similar type of PIP into one and have a common enhanced experience for web users enabling best practices across industry being used in web analytics problem space
•  Enabled engagement increase by 40% and revenue attributed to web page by 10%

Feb 2021 – Jul 2022 · 1 yr 5 mos

• Build new ML capabilities for home improvement retailer to maximise marketing outputs through Uplift Modelling
•  Built an incremental revenue generating framework using causal Machine Learning techniques
•  Helped a Fortune 20 retailer generate 2x incremental revenue from Services marketing campaign
• Built an Acquisition Modelling framework to enhance audience selection strategy for direct mailers for a fortune 20 retailer:
•  Built a propensity framework to identify high propensity audience who had not been purchasing in client acquired premium products helping drive more revenue for the business partners
•  Drive 0.34% incremental response lift from Decor campaigns also thereby increasing Decor customer base
• Developed several Latency Based Models for better targeting of audience for decor campaigns:
•  Developed a XGBoost framework to predict an audience for catalog marketing campaign that would reach the consumers post 1.5 month period
•  Incremental revenue of 150M$ generated through audience from the campaign
• Set Décor Propensity Models for an immediate business use case ensuring quality and timeliness:
•  Setup a propensity structure using predictive modelling algorithm (XGBoost) to identify probable Décor purchaser for décor campaigns
•  Generated incremental CTRs (+35%) and ROAS (+141%) from the campaign Store Proximity Analysis for Hyperlocal Marketing effort:
•  Setup a structure to identify best stores for a Fortune 20 retailer based on probabilistic purchase happening in the stores across US to help them put more store associates in priority stores and role special
• Set up a framework to help Hyperlocal marketing team better roll out localised campaigns near the store region and identify placement of stores associates accordingly
•  Helped client generate 75 million $ from hyperlocal marketing efforts and increase return per dollar by 20%

Jul 2019 – Jan 2021 · 1 yr 6 mos

• Built XGBoost models to support audience selection process for various types of Email,direct mail and Catalog campaigns
• Helped clients with the measurement of various supported campaigns using Tableau as a tool
• Helped client support weekly campaign by assisting them with a weekly audience file based on model performance
• Helped client by carrying out Do not mail process across the whole project to avoid targeting of individuals who have opted out from receiving any campaign
• Carried out transitions from SAS to Python for various processes, to help client with easy movement of processes to new platform
• Helped client identify benchmark lift values for campaigns, so as to gauge the campaign being successful or not

Jun 2017 – Jul 2017 · 1 mo · Lucknow, Uttar Pradesh, India

• Worked in the Signal Directorate of the organisation and prepared a project on Japanese railways